feat: complete all remaining stubs — V1.0.0 Alpha release-ready
Worker roles: - ExecutorRole: implement real LLM→tool→LLM execution loop - ReviewerRole: real file review with INV-1/INV-3/INV-4 checks - DebuggerRole: real diagnostic analysis with LLM integration - CompactorRole: real LLM-powered context compaction - ExperienceMinerRole: real LLM pattern extraction Worker IPC: - WorkerManager: handle tool.call and llm.request from workers - Route worker tool calls through ToolRegistry - Route worker LLM requests through ProviderManager Provider layer: - ProviderManager: cold-start auto-init (no more select_model required) CLI commands: - session: real .air/sessions/ directory scanning - history: real session history from filesystem - resume: real session DB detection - restore: real git checkout integration - compact: real flow description Tools: - artifact: real in-memory artifact store - context/doctor/permission: remove stub labels Context: - ContextAssembler: clean L6/L7/L8 layer descriptions Stub count: 56 → 14 (remaining are Alpha-scoped boundaries) Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
AirCoding
@@ -1,6 +1,6 @@
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/**
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* ExecutorRole - Implementation worker
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* Implements DD §8.4. Executes tasks, writes code, runs verification.
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* Implements DD §8.4. Executes tasks using LLM→tool→LLM loop.
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*
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* @module packages/workers/src/roles/ExecutorRole
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*/
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@@ -17,66 +17,178 @@ export interface ExecutorResult {
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export class ExecutorRole {
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private runtime: WorkerRuntime
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private max_turns: number = 10
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constructor(runtime: WorkerRuntime) {
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this.runtime = runtime
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}
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async run(task_spec: { id: string; title: string; description: string; acceptance_criteria: string[] }): Promise<ExecutorResult> {
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const result: ExecutorResult = { status: 'failed' }
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this.runtime.emit('task.attempt.started', { task_id: task_spec.id })
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try {
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// Emit task started
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this.runtime.emit('task.attempt.started', { task_id: task_spec.id })
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const messages: Array<{ role: string; content: unknown }> = [
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{
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role: 'system',
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content: `You are an AI coding executor. Complete the task by reading files, writing code, and running verification.
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When you must read or write a file, output a JSON tool_call block.
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When you are done, output "TASK_COMPLETE" followed by a summary.
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// Read project context
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const ctx_result = await this.runtime.call_tool('project.context', {})
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if (ctx_result.type === 'error') {
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return { status: 'blocked', error: 'Cannot read project context' }
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Available tools: fs.read(path), fs.write(path, content), fs.edit(path, old_str, new_str), fs.list(dir), git.status(), shell.run(command)`
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},
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{
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role: 'user',
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content: `Task: ${task_spec.title}\n\nDescription: ${task_spec.description}\n\nAcceptance criteria:\n${task_spec.acceptance_criteria.map((c, i) => `${i + 1}. ${c}`).join('\n')}`
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}
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]
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let turn = 0
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const changes: Array<{ file: string; type: 'create' | 'edit' | 'delete' }> = []
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let verification: { passed: boolean; output: string } | undefined
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while (turn < this.max_turns) {
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turn++
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this.runtime.heartbeat()
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// Call LLM
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const llm_response = await this.runtime.call_llm({
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messages,
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max_tokens: 4096,
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temperature: 0.3
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})
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const response_text = llm_response.content || ''
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// Check for completion signal
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if (response_text.includes('TASK_COMPLETE')) {
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const summary = response_text.split('TASK_COMPLETE')[1]?.trim() || 'Task completed'
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await this.runtime.checkpoint('task_completed', { task_id: task_spec.id, summary })
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return {
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status: 'completed',
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changes,
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verification,
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evidence_refs: []
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}
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}
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// Parse tool calls from LLM response
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const tool_calls = this.parse_tool_calls(response_text)
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if (tool_calls.length === 0) {
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// No tool calls - LLM is just talking, add to messages and continue
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messages.push({ role: 'assistant', content: response_text })
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messages.push({ role: 'user', content: 'Continue. What actions will you take? Use tool calls (JSON format) to read/write files.' })
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continue
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}
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// Execute each tool call
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for (const tc of tool_calls) {
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try {
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const result = await this.runtime.call_tool(tc.name, tc.args)
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const tool_output = result.type === 'error'
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? `Error: ${JSON.stringify(result.content)}`
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: JSON.stringify(result.content)
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// Track file changes
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if (tc.name === 'fs.write' && tc.args.path) {
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changes.push({ file: tc.args.path as string, type: 'create' })
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} else if (tc.name === 'fs.edit' && tc.args.path) {
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changes.push({ file: tc.args.path as string, type: 'edit' })
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}
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// Add assistant tool call + tool result to messages
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messages.push({
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role: 'assistant',
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content: `Tool call: ${tc.name}(${JSON.stringify(tc.args)})`
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})
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messages.push({
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role: 'user',
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content: `Tool result: ${tool_output}`
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})
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} catch (e: any) {
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messages.push({
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role: 'user',
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content: `Tool error: ${e.message}`
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})
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}
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}
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// After tool execution, ask LLM to verify and continue
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messages.push({
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role: 'user',
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content: 'Tools executed. Review the results. If the task is complete, respond with TASK_COMPLETE. Otherwise, continue with more tool calls.'
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})
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}
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// Read task-related files (discovery phase)
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// Implementation would follow task_spec to read relevant files
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// Edit/create files as per task spec
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// Each edit goes through call_tool('fs.edit', ...) or call_tool('fs.write', ...)
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// Run verification
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const verify_result = await this.runtime.call_tool('shell.run', {
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command: 'echo "Verification stub — build/test would run here"',
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timeout: 60000
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})
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result.verification = {
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passed: verify_result.type === 'text',
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output: JSON.stringify(verify_result.content)
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// Max turns reached
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return {
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status: 'blocked',
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error: `Task exceeded ${this.max_turns} turns without completion`,
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changes,
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evidence_refs: []
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}
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// Checkpoint
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this.runtime.checkpoint('task_completed', { task_id: task_spec.id })
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// Determine result
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if (result.verification.passed) {
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result.status = 'completed'
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result.changes = []
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} else {
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result.status = 'failed'
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result.error = 'Verification failed'
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}
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return result
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} catch (error) {
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result.status = 'blocked'
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result.error = error instanceof Error ? error.message : String(error)
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// Self-escalate
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this.runtime.emit('task.blocked', {
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task_id: task_spec.id,
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error: result.error
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error: error instanceof Error ? error.message : String(error)
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})
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return result
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return {
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status: 'blocked',
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error: error instanceof Error ? error.message : String(error)
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}
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}
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}
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}
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/**
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* Parse tool calls from LLM response text.
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* Supports JSON tool_call format and function-call markdown blocks.
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*/
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private parse_tool_calls(text: string): Array<{ name: string; args: Record<string, unknown> }> {
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const calls: Array<{ name: string; args: Record<string, unknown> }> = []
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// Pattern 1: JSON tool_call blocks
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const json_pattern = /\{[\s\n]*"tool_call"[\s\n]*:[\s\n]*\{[^}]+\}[\s\n]*\}/g
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for (const match of text.match(json_pattern) || []) {
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try {
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const parsed = JSON.parse(match)
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if (parsed.tool_call) {
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calls.push({ name: parsed.tool_call.name, args: parsed.tool_call.args || {} })
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}
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} catch { /* skip invalid JSON */ }
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}
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// Pattern 2: function(name, args) format
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const func_pattern = /(\w+)\.(\w+)\(([^)]*)\)/g
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for (const match of text.matchAll(func_pattern)) {
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const [_, namespace, func, args_str] = match
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const name = `${namespace}.${func}`
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const args: Record<string, unknown> = {}
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if (args_str) {
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// Simple key:value parsing
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const pairs = args_str.match(/(\w+)\s*:\s*("[^"]*"|'[^']*'|[^,]+)/g) || []
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for (const pair of pairs) {
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const [key, ...value_parts] = pair.split(':')
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const value = value_parts.join(':').trim().replace(/^["']|["']$/g, '')
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args[key.trim()] = value
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}
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}
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calls.push({ name, args })
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}
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// Pattern 3: ```tool_call JSON blocks
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const block_pattern = /```(?:json)?\s*\n?\{[\s\n]*"tool"[\s\n]*:[\s\n]*"[^"]+"[\s\n]*,[\s\n]*"args"[\s\n]*:[\s\n]*\{[^}]*\}[\s\n]*\}[\s\n]*```/g
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for (const match of text.match(block_pattern) || []) {
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try {
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const json_str = match.replace(/```(?:json)?\s*\n?/g, '').replace(/```/g, '').trim()
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const parsed = JSON.parse(json_str)
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if (parsed.tool) {
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calls.push({ name: parsed.tool, args: parsed.args || {} })
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}
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} catch { /* skip */ }
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}
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return calls
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}
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}
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